Global Navigation Satellite Systems (GNSS) include for example the Global Positioning System (GPS), the GLONASS system, the Galileo system, the COMPASS system, and others.
In the context of GPS for example, each satellite transmits continuously using two radio frequencies in the L-band, referred to as L1 and L2, at respective frequencies of 1575.42 MHz and 1227.60 MHz. With the ongoing modernization of the GPS, it is currently planned to use a third frequency referred to as L5 frequency at 1176.45 MHz. Two signals are transmitted on L1, one for civil users and the other for users authorized by the United States Department of Defense (DoD). One signal is transmitted on L2, intended only for DoD-authorized users, but which can be received by civil users with suitably equipped receivers. More recent GPS satellites also transmit a second signal on L2 for civil users. Each GPS signal has a carrier at the L1 and L2 frequency, a pseudo-random number (PRN) code, and a navigation message containing information about the satellite orbit, the satellite health status, various correction data, status messages and other data messages. Two different PRN codes are transmitted by each satellite: a coarse acquisition (C/A) code and a precision (P/Y) code which is encrypted for DoD-authorized users. Each C/A code is a unique sequence of 1023 bits, which is repeated each millisecond.
Other GNSS systems likewise have satellites which transmit multiple signals on multiple carrier frequencies.
FIG. 1 schematically illustrates a prior-art GNSS scenario 100. Receiver 110 receives GNSS signals from any number of satellites in view, such as from satellites 120, 130 and 140. The signals pass through the earth's ionosphere 150 and through the earth's troposphere 160. Each signal has multiple carrier frequencies, such as for example frequencies L1 and L2. Receiver 110 determines from the signals respective approximate (apparent) distances to the satellites (so called pseudo-ranges, PR1, PR2, . . . , PRm). Pseudo-range determinations are distorted by signal-path variations resulting from passage of the signals through the ionosphere 150 and the troposphere 160, and from multipath effects, as schematically illustrated by reference 170 on FIG. 1. Pseudo-ranges can be determined using the C/A code with an error of about one meter. However, the phases of the L1 and L2 carriers can be measured with an accuracy of 0.01-0.05 cycles (corresponding to pseudo-range errors of 2 mm to 1 cm). Phase measurements of the carriers are influenced by the dispersive effects of the ionosphere, which vary over time.
Due to the much higher accuracy, the processing of the phase observations is advantageous for precise GNSS positioning. However, a complication arises in that the exact number of cycles between the receiver and the satellite is a priori unknown. More specifically, the phase observations are ambiguous by an ambiguity term which is a product of an unknown integer number and the wavelength of the carrier signal. To handle these unknown integers, they can simply be estimated as floating-point numbers within the GNSS parameter estimation. The corresponding position result is called a float solution. The float solution can be improved by fixing the estimated floating-point numbers to integer values by corresponding known methods (e.g. the LAMBDA method). The GNSS parameter estimation can afterwards be recomputed with the fixed integer values for the integer ambiguities. By doing so, the number of unknowns is reduced drastically and the accuracy of the positioning result with the fixed solution is better than with the float solution (see Peter Joosten and Christian Tiberius, “Fixing the ambiguities—are you sure they are right?”, in GPS World (2000), Vol. 11, No. 5, pp. 46-51).
For certain applications, artificial observations can be computed from the original ones by forming linear combinations from the observations. This is true both for the code and the phase observations. Such linear combinations have different properties compared to the original observations. Popular linear combinations are the Melbourne-Wuebbena (MW) linear combination, the widelane linear combination, the geometric-free linear combination (also called ionospheric linear combination) and the ionospheric-free linear combination (also called geometric linear combination). Their properties are beneficial with respect to dedicated applications (see for example WO2011/034614 A2). For example, the MW linear combination eliminates the effect of the ionosphere, of the geometry, of the clocks, and of the troposphere, the geometric-free linear combination is independent of receiver clocks and geometry (orbits, station coordinates), and the ionospheric-free linear combination eliminates the first-order effect of the ionospheric path delay.
GNSS positioning accuracy is generally limited by measurement errors that can be classified as either common mode or noncommon mode. Common-mode errors have nearly identical effects on all receivers operating in a limited geographic area (e.g. 50 km). Noncommon-mode errors are distinct even for two receivers with minimal antenna separation. Relative positioning allows common-mode errors to be mitigated by differencing the observations of the rover with observations of a reference station at a known location near the rover, e.g., within 50-100 km. The reference station observations can be collected at a physical base station or estimated from observations of a network of reference stations (see for example U.S. Pat. No. 5,477,458 and U.S. Pat. No. 5,899,957).
Another way to obtain accurate positioning results is to use a technique is known as precise point positioning (PPP), also called absolute positioning, which uses a single GNSS receiver together with precise satellite orbit and clock data to reduce satellite-related error sources. A dual-frequency receiver can remove the first-order effect of the ionosphere by using the ionospheric-free linear combination. Afterwards, position solutions are accurate in a range of centimeters to decimeters. The utility of PPP is limited by the need to wait longer than desired for the float position solution to converge to centimeter accuracy. This waiting time is called convergence time. In contrast to relative positioning techniques in which common-mode errors are eliminated by differencing of observations using reference stations, PPP processing uses undifferenced carrier-phase observations so that the ambiguity terms are corrupted by satellite and receiver phase biases. Methods have been proposed in the prior art for integer ambiguity resolution in PPP processing (see for example WO2011/034614 A2 and Yang Gao, “Precise Point Positioning and Its Challenges”, Inside GNSS (2006), Vol. 1, No. 8, pp. 16-18).
A conventional way to deal with the problems of PPP is described in international application WO 2011/034614 A2. This involves generating synthetic base station data which preserves the integer nature of carrier phase data. A set of corrections is computed per satellite (a MW-bias, a code leveled clock error and a phase leveled clock error) from global network data. Using these corrections, a rover can use the MW-combination to solve widelane ambiguities and use ionospheric-free code/phase observations to solve the N1 (narrowlane) ambiguities. With fixed ambiguities, the rover can achieve cm-level accuracy positioning in real-time, meaning that there is an action (e.g., data is processed, results are computed) as soon as the required information for that action is available. The advantage of this approach is that it is insensitive to ionospheric activity, the disadvantage is that the convergence time is longer than desired.
In order to improve the convergence time, US patent publication No. 2013/0044026, filed Feb. 13, 2012 (and incorporated herein by reference in its entirety for all purposes), describes a method to make use of an ionosphere model and further derive an ionospheric phase bias per satellite in addition to other corrections (a MW-bias, a code leveled clock error and a phase leveled clock error) to generate synthetic base station data. The synthetic base station data generated with this approach preserves the integer nature of carrier phase data, and it can be used for both single and dual frequency rovers. This approach requires an ionosphere model in general, and the rover convergence time depends heavily on the accuracy of the ionosphere model provided. Therefore, it is necessary to provide not only the ionosphere model itself but also its accuracy to the methods and apparatus for the GNSS data processing.
One way to provide a rover with an ionosphere model and information on the accuracy of the ionosphere model is a satellite based augmentation system (SBAS). A SBAS is a system that supports wide-area or regional augmentation through the use of additional satellite-broadcast messages. Such systems are commonly composed of multiple ground stations, located at accurately-surveyed points. The ground stations take measurements of one or more of the GNSS satellite signals and other environmental factors which may impact the signals received by the users. Using these measurements, information messages are created and sent to one or more satellites for broadcast to the end users. Especially, a SBAS provides correction data to increase the integrity and accuracy of a single frequency, code based positioning with GNSS whereas the correction data are broadcasted by communication satellites and can be received directly with the GNSS receiver. There are several SBAS running, such as e.g. WAAS (Wide Area Augmentation System) in North America and EGNOS (European Geostationary Navigation Overlay Service) in Europe.
The main application of SBAS is precise and reliable GNSS-based aircraft navigation. Single frequency, code based positioning devices can benefit from SBAS. After applying SBAS corrections, the positioning accuracy is in the meter range. Within the SBAS framework, ionospheric vertical delays (i.e. the ionospheric delay for a signal travelling vertically through the ionosphere) at geographically fixed ionospheric grid points (IGPs) are provided. In addition to these vertical delays, the SBAS message contains grid ionospheric vertical errors (GIVEs) for the IGPs (see for example Ahmadi, R., G. S. Becker, S. R. Peck, F. Choquette, T. F. Garard, A. J. Mannucci, B. A. Iijima, and A. W. Moore (1997): “Validation analysis of the WAAS GIVE and UIVE Algorithms”. Proceedings of the 53rd Annual Meeting, Inst. Of Navigation, Alexandria, Va.).
U.S. Pat. No. 5,828,336 presents a method and a device for providing real-time wide-area differential GPS signals to allow users with a GPS receiver to obtain improved GPS positioning. The ionosphere correction system in this document uses a real-time Kalman filter to compute sun-fixed ionospheric delay maps and the associated formal error maps. The formal error map can be used to evaluate the quality of the ionospheric correction broadcast to the user, and to block the broadcast of suspect data. The formal error is determined by the total electron content (TEC) data weights, the observation geometry, the data equation, and the random-walk standard deviation (see Mannucci, A. J., Wilson, B. D, Edwards, C. D. (1993): “A New Method for Monitoring the Earth's Ionospheric Total Electron Content Using the GPS Global Network”. Proceedings of ION GPS-93, pp. 1323-1332).
Harris, I. L., A. J. Mannucci, B. A. Iijima, U. J. Lindqwister, D. Muna, X. Pi and B. D. Wilson (2001): “Ionospheric specification algorithms for precise GPS-based aircraft navigation”, Radio Science, Volume 36, Number 2, pp. 287-298, March/April 2001 discloses a method of grid ionospheric vertical error (GIVE) computation. It is a combination of a Kalman-filter based statistical error derived solely from the measurement system (which is the formal error map described in U.S. Pat. No. 5,828,336 times several scale factors), and error due to the spatial decorrelation of the ionosphere and error from converting the vertical corrections to slant paths. GIVE values are required to bound the actual error with 99.9% confidence to meet the requirement of integrity and accuracy. The scaling factors and the two additional error contributions considered in the GIVE values improve the agreement between the provided error indicator and the true error (compared to the previous approach in Mannucci, A. J., Wilson, B. D, Edwards, C. D. (1993): “A New Method for Monitoring the Earth's Ionospheric Total Electron Content Using the GPS Global Network”. Proceedings of ION GPS-93, pp. 1323-1332). Nevertheless, the GIVE is mainly based on the formal errors and therefore a direct reference to the true error of the provided delay is not given.
In view of the above, the present invention aims at providing improved accuracy information of an ionosphere model in real-time, so that the accuracy information can be efficiently used for GNSS positioning applications.